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  1. How Children and Adults Represent God's Mind.Larisa Heiphetz, Jonathan D. Lane, Adam Waytz & Liane L. Young - 2016 - Cognitive Science 40 (1):121-144.
    For centuries, humans have contemplated the minds of gods. Research on religious cognition is spread across sub-disciplines, making it difficult to gain a complete understanding of how people reason about gods' minds. We integrate approaches from cognitive, developmental, and social psychology and neuroscience to illuminate the origins of religious cognition. First, we show that although adults explicitly discriminate supernatural minds from human minds, their implicit responses reveal far less discrimination. Next, we demonstrate that children's religious cognition often matches adults' implicit (...)
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  • Just Do It? Investigating the Gap Between Prediction and Action in Toddlers’ Causal Inferences.Elizabeth Baraff Bonawitz, Darlene Ferranti, Rebecca Saxe, Alison Gopnik, Andrew N. Meltzoff, James Woodward & Laura E. Schulz - 2010 - Cognition 115 (1):104-117.
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  • The Origins of Inquiry: Inductive Inference and Exploration in Early Childhood.Laura Schulz - 2012 - Trends in Cognitive Sciences 16 (7):382-389.
  • Learning to Learn Causal Models.Charles Kemp, Noah D. Goodman & Joshua B. Tenenbaum - 2010 - Cognitive Science 34 (7):1185-1243.
    Learning to understand a single causal system can be an achievement, but humans must learn about multiple causal systems over the course of a lifetime. We present a hierarchical Bayesian framework that helps to explain how learning about several causal systems can accelerate learning about systems that are subsequently encountered. Given experience with a set of objects, our framework learns a causal model for each object and a causal schema that captures commonalities among these causal models. The schema organizes the (...)
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  • Constructing a New Theory From Old Ideas and New Evidence.Marjorie Rhodes & Henry Wellman - 2013 - Cognitive Science 37 (3):592-604.
    A central tenet of constructivist models of conceptual development is that children's initial conceptual level constrains how they make sense of new evidence and thus whether exposure to evidence will prompt conceptual change. Yet little experimental evidence directly examines this claim for the case of sustained, fundamental conceptual achievements. The present study combined scaling and experimental microgenetic methods to examine the processes underlying conceptual change in the context of an important conceptual achievement of early childhood—the development of a representational theory (...)
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  • The Early Emergence and Puzzling Decline of Relational Reasoning: Effects of Knowledge and Search on Inferring Abstract Concepts.Caren M. Walker, Sophie Bridgers & Alison Gopnik - 2016 - Cognition 156:30-40.
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  • Hierarchical Bayesian Models as Formal Models of Causal Reasoning.York Hagmayer & Ralf Mayrhofer - 2013 - Argument and Computation 4 (1):36 - 45.
    (2013). Hierarchical Bayesian models as formal models of causal reasoning. Argument & Computation: Vol. 4, Formal Models of Reasoning in Cognitive Psychology, pp. 36-45. doi: 10.1080/19462166.2012.700321.
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  • Developmental Differences in Learning the Forms of Causal Relationships.Chris Lucas, Alison Gopnik & Thomas L. Griffiths - 2010 - In S. Ohlsson & R. Catrambone (eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society. Cognitive Science Society. pp. 28--52.
  • Probabilistic Models as Theories of Children's Minds.Alison Gopnik - 2011 - Behavioral and Brain Sciences 34 (4):200-201.
    My research program proposes that children have representations and learning mechanisms that can be characterized as causal models of the world Bayesian Fundamentalism.”.
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  • A Unified Account of Abstract Structure and Conceptual Change: Probabilistic Models and Early Learning Mechanisms.Alison Gopnik - 2011 - Behavioral and Brain Sciences 34 (3):129-130.
    We need not propose, as Carey does, a radical discontinuity between core cognition, which is responsible for abstract structure, and language and which are responsible for learning and conceptual change. From a probabilistic models view, conceptual structure and learning reflect the same principles, and they are both in place from the beginning.
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  • Précis of the Origin of Concepts.Susan Carey - 2011 - Behavioral and Brain Sciences 34 (3):113-124.
    A theory of conceptual development must specify the innate representational primitives, must characterize the ways in which the initial state differs from the adult state, and must characterize the processes through which one is transformed into the other. The Origin of Concepts (henceforth TOOC) defends three theses. With respect to the initial state, the innate stock of primitives is not limited to sensory, perceptual, or sensorimotor representations; rather, there are also innate conceptual representations. With respect to developmental change, conceptual development (...)
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  • Verbal Framing of Statistical Evidence Drives Children’s Preference Inferences.Laura E. Garvin & Amanda L. Woodward - 2015 - Cognition 138:35-48.
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  • Children’s Developing Understanding of the Relation Between Variable Causal Efficacy and Mechanistic Complexity.Christopher D. Erb, David W. Buchanan & David M. Sobel - 2013 - Cognition 129 (3):494-500.
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  • From Colliding Billiard Balls to Colluding Desperate Housewives: Causal Bayes Nets as Rational Models of Everyday Causal Reasoning.York Hagmayer & Magda Osman - 2012 - Synthese 189 (S1):17-28.
    Many of our decisions pertain to causal systems. Nevertheless, only recently has it been claimed that people use causal models when making judgments, decisions and predictions, and that causal Bayes nets allow us to formally describe these inferences. Experimental research has been limited to simple, artificial problems, which are unrepresentative of the complex dynamic systems we successfully deal with in everyday life. For instance, in social interactions, we can explain the actions of other's on the fly and we can generalize (...)
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  • When Children Are Better Learners Than Adults: Developmental Differences in Learning the Forms of Causal Relationships.Christopher G. Lucas, Sophie Bridgers, Thomas L. Griffiths & Alison Gopnik - 2014 - Cognition 131 (2):284-299.
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  • Anomalous Evidence, Confidence Change, and Theory Change.Joshua A. Hemmerich, Kellie Van Voorhis & Jennifer Wiley - 2016 - Cognitive Science 40 (6):1534-1560.
    A novel experimental paradigm that measured theory change and confidence in participants' theories was used in three experiments to test the effects of anomalous evidence. Experiment 1 varied the amount of anomalous evidence to see if “dose size” made incremental changes in confidence toward theory change. Experiment 2 varied whether anomalous evidence was convergent or replicating. Experiment 3 varied whether participants were provided with an alternative theory that explained the anomalous evidence. All experiments showed that participants' confidence changes were commensurate (...)
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  • Science Is Awe-Some: The Emotional Antecedents of Science Learning.Piercarlo Valdesolo, Andrew Shtulman & Andrew S. Baron - 2017 - Emotion Review 9 (3):215-221.
    Scientists from Einstein to Sagan have linked emotions like awe with the motivation for scientific inquiry, but no research has tested this possibility. Theoretical and empirical work from affective science, however, suggests that awe might be unique in motivating explanation and exploration of the physical world. We synthesize theories of awe with theories of the cognitive mechanisms related to learning, and offer a generative theoretical framework that can be used to test the effect of this emotion on early science learning.
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